An Approximate Dynamic Programming Algorithm for the Allocation of High-Voltage Transformer Spares in the Electric Grid

Abstract

This paper addresses the problem of allocating high-voltage transformer spares throughout the electric grid to mitigate the risk of random transformer failures. With this application we investigate the use of approximate dynamic programming (ADP) for solving large scale stochastic facility location problems. The ADP algorithms that we develop consistently obtain near optimal solutions for problems where the optimum is computable and outperform a standard heuristic on more complex problems. Our computational results show that the ADP methodology can be applied to large scale problems that cannot be solved with exact algorithms.

Robust policies for the transformer acquisition and allocation problem

“…In [3] we explore the locational aspects of transformer allocation under uncertainty by introducing an algorithm that determines near optimal locations for spare transformers and also estimate the optimal size of the spare population. This model is tested on actual PJM system data and on a range simulated data sets.…”